TY - GEN
T1 - Unique on Facebook
T2 - 21st ACM Internet Measurement Conference
AU - Gonzalez-Cabañas, Jose
AU - Cuevas, Angel
AU - Cuevas, Ruben
AU - Lopez-Fernandez, Juan
AU - Garcia, David
N1 - Funding Information:
This research received funding from the European Union’s Horizon 2020 innovation action programme under the PIMCITY project (Grant 871370) and the TESTABLE project (Grant 101019206); the Ministerio de Economía, Industria y Competitividad, Spain, and the European Social Fund(EU), under the Ramón y Cajal programme (Grant RyC-2015-17732); the Ministerio de Educación, Cultura y Deporte, Spain, through the FPU programme (Grant FPU16/05852); the Agencia Estatal de Investigación (AEI) under the ACHILLES project (Grant PID2019-104207RB-I00/AEI/10.13039/501100011033); the Community of Madrid synergic project EMPATIA-CM (Grant Y2018/TCS-5046); the Fundación BBVA under the project AERIS; and the Vienna Science and Technology Fund through the project “Emotional Well-Being in the Digital Society” (Grant VRG16-005).
Publisher Copyright:
© 2021 ACM.
PY - 2021/11/2
Y1 - 2021/11/2
N2 - The privacy of an individual is bounded by the ability of a third party to reveal their identity. Certain data items such as a passport ID or a mobile phone number may be used to uniquely identify a person. These are referred to as Personal Identifiable Information (PII) items. Previous literature has also reported that, in datasets including millions of users, a combination of several non-PII items (which alone are not enough to identify an individual) can uniquely identify an individual within the dataset. In this paper, we define a data-driven model to quantify the number of interests from a user that make them unique on Facebook. To the best of our knowledge, this represents the first study of individuals' uniqueness at the world population scale. Besides, users' interests are actionable non-PII items that can be used to define ad campaigns and deliver tailored ads to Facebook users. We run an experiment through 21 Facebook ad campaigns that target three of the authors of this paper to prove that, if an advertiser knows enough interests from a user, the Facebook Advertising Platform can be systematically exploited to deliver ads exclusively to a specific user. We refer to this practice as nanotargeting. Finally, we discuss the harmful risks associated with nanotargeting such as psychological persuasion, user manipulation, or blackmailing, and provide easily implementable countermeasures to preclude attacks based on nanotargeting campaigns on Facebook.
AB - The privacy of an individual is bounded by the ability of a third party to reveal their identity. Certain data items such as a passport ID or a mobile phone number may be used to uniquely identify a person. These are referred to as Personal Identifiable Information (PII) items. Previous literature has also reported that, in datasets including millions of users, a combination of several non-PII items (which alone are not enough to identify an individual) can uniquely identify an individual within the dataset. In this paper, we define a data-driven model to quantify the number of interests from a user that make them unique on Facebook. To the best of our knowledge, this represents the first study of individuals' uniqueness at the world population scale. Besides, users' interests are actionable non-PII items that can be used to define ad campaigns and deliver tailored ads to Facebook users. We run an experiment through 21 Facebook ad campaigns that target three of the authors of this paper to prove that, if an advertiser knows enough interests from a user, the Facebook Advertising Platform can be systematically exploited to deliver ads exclusively to a specific user. We refer to this practice as nanotargeting. Finally, we discuss the harmful risks associated with nanotargeting such as psychological persuasion, user manipulation, or blackmailing, and provide easily implementable countermeasures to preclude attacks based on nanotargeting campaigns on Facebook.
UR - http://www.scopus.com/inward/record.url?scp=85118970017&partnerID=8YFLogxK
U2 - 10.1145/3487552.3487861
DO - 10.1145/3487552.3487861
M3 - Conference paper
AN - SCOPUS:85118970017
SP - 464
EP - 479
BT - IMC 2021 - Proceedings of the 2021 ACM Internet Measurement Conference
PB - Association of Computing Machinery
Y2 - 2 November 2021 through 4 November 2021
ER -